Evidence map›Paper›PMID 27922122›Full record

ArticleScientific reports2016

Identification of critical paralog groups with indispensable roles in the regulation of signaling flow.

Dezso Modos, Johanne Brooks, David Fazekas, Eszter Ari, Tibor Vellai, Peter Csermely, Tamas Korcsmaros, Katalin Lenti

Abstract read
In one paragraph

Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Zebrafish ParalogsJournal of developmental biology · 2021
    Article
  3. Double missense mutations in cardiac myosin-binding protein C and myopalladin genes: A case report with diffuse coronary disease, complete atrioventricular block, and progression to dilated cardiomyopathy.Annals of noninvasive electrocardiology : the official journal of the International Society for Holter and Noninvasive Electrocardiology, Inc · 2020
    Article
  4. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Dezso ModosDepartment of Morphology and Physiology, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary.
Johanne BrooksGut Health and Food Safety Programme, Institute of Food Research, Norwich Research Park, Norwich, UK.
David FazekasDepartment of Genetics, Eotvos Lorand University, Budapest, Hungary.
Eszter AriDepartment of Genetics, Eotvos Lorand University, Budapest, Hungary.
Tibor VellaiDepartment of Genetics, Eotvos Lorand University, Budapest, Hungary.
Peter CsermelyDepartment of Medical Chemistry, Semmelweis University, Budapest, Hungary.
Tamas KorcsmarosDepartment of Genetics, Eotvos Lorand University, Budapest, Hungary.
Katalin LentiDepartment of Morphology and Physiology, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary.

Funding

Biotechnology and Biological Sciences Research Council BB/J004529/1Wellcome Trust
6 · The paper itself

Abstract

Extensive cross-talk between signaling pathways is required to integrate the myriad of extracellular signal combinations at the cellular level. Gene duplication events may lead to the emergence of novel functions, leaving groups of similar genes - termed paralogs - in the genome. To distinguish critical paralog groups (CPGs) from other paralogs in human signaling networks, we developed a signaling network-based method using cross-talk annotation and tissue-specific signaling flow analysis. 75 CPGs were found with higher degree, betweenness centrality, closeness, and 'bowtieness' when compared to other paralogs or other proteins in the signaling network. CPGs had higher diversity in all these measures, with more varied biological functions and more specific post-transcriptional regulation than non-critical paralog groups (non-CPG). Using TGF-beta, Notch and MAPK pathways as examples, SMAD2/3, NOTCH1/2/3 and MEK3/6-p38 CPGs were found to regulate the signaling flow of their respective pathways. Additionally, CPGs showed a higher mutation rate in both inherited diseases and cancer, and were enriched in drug targets. In conclusion, the results revealed two distinct types of paralog groups in the signaling network: CPGs and non-CPGs. Thus highlighting the importance of CPGs as compared to non-CPGs in drug discovery and disease pathogenesis.

Indexed as

Computational BiologySignal TransductionDatabases, GeneticHumansOrgan SpecificityWorkflow

Identifiers

PMID27922122
PMCPMC5138592

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.